In [1]:
import pandas as pd
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt 

import warnings
from warnings import filterwarnings
filterwarnings('ignore')

Understanding use case - Running ETL pipeline - EDA - Conclusions¶

Performing basic analysis on IPL (Indian premier league)¶

In [2]:
match_data = pd.read_csv(r'C:\DA_BA_material/matches.csv')

deliveries_data = pd.read_csv(r'C:\DA_BA_material/deliveries.csv')
In [3]:
match_data.head(4)
Out[3]:
id season city date team1 team2 toss_winner toss_decision result dl_applied winner win_by_runs win_by_wickets player_of_match venue umpire1 umpire2 umpire3
0 1 2017 Hyderabad 4/5/2017 Sunrisers Hyderabad Royal Challengers Bangalore Royal Challengers Bangalore field normal 0 Sunrisers Hyderabad 35 0 Yuvraj Singh Rajiv Gandhi International Stadium, Uppal AY Dandekar NJ Llong NaN
1 2 2017 Pune 4/6/2017 Mumbai Indians Rising Pune Supergiant Rising Pune Supergiant field normal 0 Rising Pune Supergiant 0 7 SPD Smith Maharashtra Cricket Association Stadium A Nand Kishore S Ravi NaN
2 3 2017 Rajkot 4/7/2017 Gujarat Lions Kolkata Knight Riders Kolkata Knight Riders field normal 0 Kolkata Knight Riders 0 10 CA Lynn Saurashtra Cricket Association Stadium Nitin Menon CK Nandan NaN
3 4 2017 Indore 4/8/2017 Rising Pune Supergiant Kings XI Punjab Kings XI Punjab field normal 0 Kings XI Punjab 0 6 GJ Maxwell Holkar Cricket Stadium AK Chaudhary C Shamshuddin NaN
In [4]:
match_data.columns
Out[4]:
Index(['id', 'season', 'city', 'date', 'team1', 'team2', 'toss_winner',
       'toss_decision', 'result', 'dl_applied', 'winner', 'win_by_runs',
       'win_by_wickets', 'player_of_match', 'venue', 'umpire1', 'umpire2',
       'umpire3'],
      dtype='object')
In [5]:
match_data.shape ### total amount of matches played
Out[5]:
(636, 18)
In [6]:
type(match_data.shape)
Out[6]:
tuple
In [7]:
match_data.shape[0]
Out[7]:
636
In [ ]:
In [ ]:
In [8]:
match_data['city'].unique()
Out[8]:
array(['Hyderabad', 'Pune', 'Rajkot', 'Indore', 'Bangalore', 'Mumbai',
       'Kolkata', 'Delhi', 'Chandigarh', 'Kanpur', 'Jaipur', 'Chennai',
       'Cape Town', 'Port Elizabeth', 'Durban', 'Centurion',
       'East London', 'Johannesburg', 'Kimberley', 'Bloemfontein',
       'Ahmedabad', 'Cuttack', 'Nagpur', 'Dharamsala', 'Kochi',
       'Visakhapatnam', 'Raipur', 'Ranchi', 'Abu Dhabi', 'Sharjah', nan],
      dtype=object)
In [9]:
match_data['team1'].unique()
Out[9]:
array(['Sunrisers Hyderabad', 'Mumbai Indians', 'Gujarat Lions',
       'Rising Pune Supergiant', 'Royal Challengers Bangalore',
       'Kolkata Knight Riders', 'Delhi Daredevils', 'Kings XI Punjab',
       'Chennai Super Kings', 'Rajasthan Royals', 'Deccan Chargers',
       'Kochi Tuskers Kerala', 'Pune Warriors', 'Rising Pune Supergiants'],
      dtype=object)
In [ ]:
In [10]:
match_data['toss_winner'].value_counts()
Out[10]:
Mumbai Indians                 85
Kolkata Knight Riders          78
Delhi Daredevils               72
Royal Challengers Bangalore    70
Kings XI Punjab                68
Chennai Super Kings            66
Rajasthan Royals               63
Deccan Chargers                43
Sunrisers Hyderabad            35
Pune Warriors                  20
Gujarat Lions                  15
Kochi Tuskers Kerala            8
Rising Pune Supergiants         7
Rising Pune Supergiant          6
Name: toss_winner, dtype: int64
In [11]:
match_data['toss_winner'].value_counts().index[0]
Out[11]:
'Mumbai Indians'
In [ ]:
In [12]:
match_data['player_of_match'].value_counts().index[0]
Out[12]:
'CH Gayle'

Performing In-depth analysis on performance of a specific player¶

In [13]:
deliveries_data['batsman'].unique()
Out[13]:
array(['DA Warner', 'S Dhawan', 'MC Henriques', 'Yuvraj Singh',
       'DJ Hooda', 'BCJ Cutting', 'CH Gayle', 'Mandeep Singh', 'TM Head',
       'KM Jadhav', 'SR Watson', 'Sachin Baby', 'STR Binny', 'S Aravind',
       'YS Chahal', 'TS Mills', 'A Choudhary', 'PA Patel', 'JC Buttler',
       'RG Sharma', 'N Rana', 'AT Rayudu', 'KH Pandya', 'KA Pollard',
       'HH Pandya', 'TG Southee', 'AM Rahane', 'MA Agarwal', 'SPD Smith',
       'BA Stokes', 'MS Dhoni', 'JJ Roy', 'BB McCullum', 'SK Raina',
       'AJ Finch', 'KD Karthik', 'G Gambhir', 'CA Lynn', 'MK Tiwary',
       'DT Christian', 'HM Amla', 'M Vohra', 'WP Saha', 'AR Patel',
       'GJ Maxwell', 'DA Miller', 'Vishnu Vinod', 'Iqbal Abdulla',
       'P Negi', 'AP Tare', 'SW Billings', 'KK Nair', 'SV Samson',
       'RR Pant', 'CH Morris', 'CR Brathwaite', 'PJ Cummins', 'A Mishra',
       'S Nadeem', 'Z Khan', 'DR Smith', 'DS Kulkarni', 'P Kumar',
       'Basil Thampi', 'RV Uthappa', 'MK Pandey', 'YK Pathan', 'SA Yadav',
       'CR Woakes', 'SP Narine', 'Harbhajan Singh', 'AB de Villiers',
       'CJ Anderson', 'F du Plessis', 'RA Tripathi', 'R Bhatia',
       'DL Chahar', 'A Zampa', 'AB Dinda', 'Imran Tahir', 'NV Ojha',
       'V Shankar', 'Rashid Khan', 'B Kumar', 'MP Stoinis', 'MM Sharma',
       'VR Aaron', 'V Kohli', 'MJ McClenaghan', 'Ankit Sharma',
       'SN Thakur', 'RD Chahar', 'LH Ferguson', 'C de Grandhomme',
       'Bipul Sharma', 'SS Iyer', 'EJG Morgan', 'KC Cariappa',
       'Sandeep Sharma', 'Ishan Kishan', 'JD Unadkat', 'AF Milne',
       'S Badree', 'AD Mathews', 'Mohammed Shami', 'Mohammad Nabi',
       'I Sharma', 'RA Jadeja', 'AJ Tye', 'KS Williamson', 'SE Marsh',
       'Shakib Al Hasan', 'JP Faulkner', 'MG Johnson', 'K Rabada',
       'AD Nath', 'NM Coulter-Nile', 'Kuldeep Yadav', 'UT Yadav',
       'Washington Sundar', 'KV Sharma', 'DM Bravo', 'AR Bawne',
       'SP Jackson', 'MJ Guptill', 'Anureet Singh', 'IK Pathan',
       'Ankit Soni', 'JJ Bumrah', 'SL Malinga', 'PJ Sangwan', 'S Kaul',
       'LMP Simmons', 'MN Samuels', 'Swapnil Singh', 'R Tewatia',
       'MM Patel', 'SS Tiwary', 'TA Boult', 'CJ Jordan', 'IR Jaggi',
       'PP Chawla', 'AS Rajpoot', 'SC Ganguly', 'RT Ponting', 'DJ Hussey',
       'Mohammad Hafeez', 'R Dravid', 'W Jaffer', 'JH Kallis', 'CL White',
       'MV Boucher', 'B Akhil', 'AA Noffke', 'SB Joshi', 'ML Hayden',
       'MEK Hussey', 'JDP Oram', 'S Badrinath', 'K Goel', 'JR Hopes',
       'KC Sangakkara', 'SM Katich', 'T Kohli', 'M Kaif', 'DS Lehmann',
       'M Rawat', 'D Salunkhe', 'SK Warne', 'SK Trivedi', 'V Sehwag',
       'L Ronchi', 'ST Jayasuriya', 'DJ Thornely', 'PR Shah', 'AM Nayar',
       'SM Pollock', 'S Chanderpaul', 'LRPL Taylor', 'AC Gilchrist',
       'Y Venugopal Rao', 'VVS Laxman', 'A Symonds', 'SB Styris',
       'AS Yadav', 'SB Bangar', 'WPUJC Vaas', 'RP Singh', 'LR Shukla',
       'DPMD Jayawardene', 'S Sohal', 'B Lee', 'WA Mota', 'Kamran Akmal',
       'Shahid Afridi', 'DJ Bravo', 'MA Khote', 'A Nehra', 'GC Smith',
       'Pankaj Singh', 'RR Sarwan', 'S Sreesanth', 'VRV Singh',
       'R Vinay Kumar', 'AB Agarkar', 'M Kartik', 'Shoaib Malik',
       'MF Maharoof', 'VY Mahesh', 'TM Srivastava', 'B Chipli',
       'DW Steyn', 'DB Das', 'HH Gibbs', 'DNT Zoysa', 'D Kalyankrishna',
       'SA Asnodkar', 'Sohail Tanvir', 'Salman Butt', 'BJ Hodge',
       'Umar Gul', 'SP Fleming', 'S Vidyut', 'JA Morkel', 'LPC Silva',
       'DB Ravi Teja', 'Misbah-ul-Haq', 'YV Takawale', 'RR Raje',
       'Mohammad Asif', 'GD McGrath', 'Joginder Sharma', 'MS Gony',
       'M Muralitharan', 'M Ntini', 'DT Patil', 'A Kumble', 'S Anirudha',
       'CK Kapugedera', 'A Chopra', 'T Taibu', 'J Arunkumar', 'PP Ojha',
       'SP Goswami', 'SR Tendulkar', 'U Kaul', 'TM Dilshan',
       'AD Mascarenhas', 'Niraj Patel', 'LA Pomersbach', 'Younis Khan',
       'PM Sarvesh Kumar', 'DP Vijaykumar', 'Shoaib Akhtar',
       'Abdur Razzak', 'H Das', 'SD Chitnis', 'CRD Fernando',
       'VS Yeligati', 'L Balaji', 'A Mukund', 'RR Powar', 'JP Duminy',
       'A Flintoff', 'T Thushara', 'JD Ryder', 'KP Pietersen',
       'T Henderson', 'Kamran Khan', 'RS Bopara', 'R Bishnoi',
       'FH Edwards', 'PC Valthaty', 'RJ Quiney', 'AS Raut',
       'Yashpal Singh', 'M Manhas', 'AA Bilakhia', 'AN Ghosh',
       'BAW Mendis', 'DL Vettori', 'MN van Wyk', 'RE van der Merwe',
       'TL Suman', 'Shoaib Ahmed', 'GR Napier', 'KP Appanna',
       'LA Carseldine', 'SM Harwood', 'M Vijay', 'SB Jakati', 'RJ Harris',
       'D du Preez', 'M Morkel', 'J Botha', 'C Nanda', 'Mashrafe Mortaza',
       'A Singh', 'GJ Bailey', 'AB McDonald', 'Y Nagar', 'SS Shaikh',
       'R Ashwin', 'Mohammad Ashraful', 'CA Pujara', 'OA Shah',
       'Anirudh Singh', 'Jaskaran Singh', 'R Sathish', 'R McLaren',
       'AA Jhunjhunwala', 'P Dogra', 'A Uniyal', 'MS Bisla', 'YA Abdulla',
       'JM Kemp', 'S Tyagi', 'RS Gavaskar', 'SE Bond', 'S Ladda',
       'DP Nannes', 'MJ Lumb', 'DR Martyn', 'S Narwal', 'AB Barath',
       'FY Fazal', 'AC Voges', 'MD Mishra', 'J Theron', 'SJ Srivastava',
       'R Sharma', 'SW Tait', 'KB Arun Karthik', 'KAJ Roach',
       'PD Collingwood', 'CK Langeveldt', 'VS Malik', 'A Mithun',
       'AP Dole', 'AN Ahmed', 'RS Sodhi', 'DE Bollinger', 'S Sriram',
       'B Sumanth', 'C Madan', 'AG Paunikar', 'MR Marsh', 'Harmeet Singh',
       'RV Gomez', 'AUK Pathan', 'UBT Chand', 'DJ Jacobs', 'Sunny Singh',
       'NJ Rimmington', 'AL Menaria', 'WD Parnell', 'JJ van der Wath',
       'R Ninan', 'MS Wade', 'TD Paine', 'SB Wagh', 'AC Thomas',
       'JEC Franklin', 'DH Yagnik', 'S Randiv', 'BJ Haddin',
       'NLTC Perera', 'NL McCullum', 'JE Taylor', 'J Syed Mohammad',
       'RN ten Doeschate', 'TR Birt', 'AG Murtaza', 'Harpreet Singh',
       'M Klinger', 'AC Blizzard', 'I Malhotra', 'L Ablish', 'CA Ingram',
       'P Parameswaran', 'CJ Ferguson', 'AA Chavan', 'ND Doshi',
       'Y Gnaneswara Rao', 'S Rana', 'BA Bhatt', 'RE Levi', 'KK Cooper',
       'HV Patel', 'DAJ Bracewell', 'DJ Harris', 'GB Hogg', 'RR Bhatkal',
       'CJ McKay', 'N Saini', 'Azhar Mahmood', 'RJ Peterson',
       'KMDN Kulasekara', 'A Ashish Reddy', 'V Pratap Singh',
       'BB Samantray', 'MJ Clarke', 'Gurkeerat Singh', 'AP Majumdar',
       'PA Reddy', 'K Upadhyay', 'P Awana', 'AD Russell', 'A Chandila',
       'Sunny Gupta', 'MC Juneja', 'GH Vihari', 'MDKJ Perera', 'R Shukla',
       'B Laughlin', 'BMAJ Mendis', 'R Rampaul', 'SMSM Senanayake',
       'BJ Rohrer', 'KL Rahul', 'Q de Kock', 'R Dhawan', 'LJ Wright',
       'IC Pandey', 'CM Gautam', 'X Thalaivan Sargunam', 'DJG Sammy',
       'KW Richardson', 'UA Birla', 'Parvez Rasool', 'PV Tambe',
       'NJ Maddinson', 'JDS Neesham', 'MA Starc', 'BR Dunk', 'RR Rossouw',
       'Shivam Sharma', 'VH Zol', 'BE Hendricks', 'S Gopal', 'M de Lange',
       'JO Holder', 'Karanveer Singh', 'SA Abbott', 'J Suchith',
       'RG More', 'D Wiese', 'SN Khan', 'DJ Muthuswami', 'C Munro',
       'P Sahu', 'KJ Abbott', 'M Ashwin', 'NS Naik', 'PSP Handscomb',
       'J Yadav', 'UT Khawaja', 'F Behardien', 'BB Sran', 'S Kaushik',
       'ER Dwivedi'], dtype=object)
In [14]:
filt = deliveries_data['batsman']=='V Kohli'
In [15]:
df_kohli = deliveries_data[filt]
In [16]:
df_kohli.columns
Out[16]:
Index(['match_id', 'inning', 'batting_team', 'bowling_team', 'over', 'ball',
       'batsman', 'non_striker', 'bowler', 'is_super_over', 'wide_runs',
       'bye_runs', 'legbye_runs', 'noball_runs', 'penalty_runs',
       'batsman_runs', 'extra_runs', 'total_runs', 'player_dismissed',
       'dismissal_kind', 'fielder'],
      dtype='object')
In [17]:
df_kohli
Out[17]:
match_id inning batting_team bowling_team over ball batsman non_striker bowler is_super_over ... bye_runs legbye_runs noball_runs penalty_runs batsman_runs extra_runs total_runs player_dismissed dismissal_kind fielder
2590 12 1 Royal Challengers Bangalore Mumbai Indians 1 2 V Kohli CH Gayle TG Southee 0 ... 0 0 0 0 0 1 1 NaN NaN NaN
2591 12 1 Royal Challengers Bangalore Mumbai Indians 1 3 V Kohli CH Gayle TG Southee 0 ... 0 0 0 0 1 0 1 NaN NaN NaN
2593 12 1 Royal Challengers Bangalore Mumbai Indians 1 5 V Kohli CH Gayle TG Southee 0 ... 0 0 0 0 0 0 0 NaN NaN NaN
2594 12 1 Royal Challengers Bangalore Mumbai Indians 1 6 V Kohli CH Gayle TG Southee 0 ... 0 0 0 0 1 0 1 NaN NaN NaN
2597 12 1 Royal Challengers Bangalore Mumbai Indians 2 1 V Kohli CH Gayle Harbhajan Singh 0 ... 0 0 0 0 0 0 0 NaN NaN NaN
... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...
150410 636 2 Royal Challengers Bangalore Sunrisers Hyderabad 12 5 V Kohli AB de Villiers Bipul Sharma 0 ... 0 0 0 0 1 0 1 NaN NaN NaN
150413 636 2 Royal Challengers Bangalore Sunrisers Hyderabad 13 2 V Kohli AB de Villiers BB Sran 0 ... 0 0 0 0 6 0 6 NaN NaN NaN
150414 636 2 Royal Challengers Bangalore Sunrisers Hyderabad 13 3 V Kohli AB de Villiers BB Sran 0 ... 0 0 0 0 2 0 2 NaN NaN NaN
150415 636 2 Royal Challengers Bangalore Sunrisers Hyderabad 13 4 V Kohli AB de Villiers BB Sran 0 ... 0 0 0 0 2 0 2 NaN NaN NaN
150416 636 2 Royal Challengers Bangalore Sunrisers Hyderabad 13 5 V Kohli AB de Villiers BB Sran 0 ... 0 0 0 0 0 0 0 V Kohli bowled NaN

3494 rows × 21 columns

In [18]:
df_kohli['dismissal_kind'].value_counts()
Out[18]:
caught               76
bowled               24
run out              14
lbw                   7
stumped               3
caught and bowled     2
Name: dismissal_kind, dtype: int64
In [ ]:
In [19]:
df_kohli['batsman_runs'].unique()
Out[19]:
array([0, 1, 6, 2, 4, 3], dtype=int64)
In [20]:
len(df_kohli[df_kohli['batsman_runs']==1])
Out[20]:
1410
In [21]:
len(df_kohli[df_kohli['batsman_runs']==2])*2
Out[21]:
484
In [22]:
len(df_kohli[df_kohli['batsman_runs']==3])*3
Out[22]:
33
In [23]:
len(df_kohli[df_kohli['batsman_runs']==4])*4
Out[23]:
1536
In [24]:
len(df_kohli[df_kohli['batsman_runs']==6])*6
Out[24]:
960
In [25]:
import plotly.express as px
import plotly.graph_objs as go
from plotly.offline import init_notebook_mode, plot, iplot
In [26]:
values = [1410,484,33,1536,960]
labels = [1,2,3,4,6]

trace = go.Pie(labels= labels, values= values, hole=0.3)

data = [trace]

fig = go.Figure(data = data)
In [27]:
fig.show()

Analyzing toss decisions across seasons of IPL¶

In [28]:
match_data.columns
Out[28]:
Index(['id', 'season', 'city', 'date', 'team1', 'team2', 'toss_winner',
       'toss_decision', 'result', 'dl_applied', 'winner', 'win_by_runs',
       'win_by_wickets', 'player_of_match', 'venue', 'umpire1', 'umpire2',
       'umpire3'],
      dtype='object')
In [29]:
match_data['Season'] = pd.to_datetime(match_data['date']).dt.year
In [30]:
match_data.columns
Out[30]:
Index(['id', 'season', 'city', 'date', 'team1', 'team2', 'toss_winner',
       'toss_decision', 'result', 'dl_applied', 'winner', 'win_by_runs',
       'win_by_wickets', 'player_of_match', 'venue', 'umpire1', 'umpire2',
       'umpire3', 'Season'],
      dtype='object')
In [ ]:
In [31]:
match_data.groupby(['Season' , 'toss_decision']).size()
Out[31]:
Season  toss_decision
2008    bat              26
        field            32
2009    bat              35
        field            22
2010    bat              39
        field            21
2011    bat              25
        field            48
2012    bat              37
        field            37
2013    bat              45
        field            31
2014    bat              19
        field            41
2015    bat              25
        field            34
2016    bat              11
        field            49
2017    bat              11
        field            48
dtype: int64
In [32]:
type(match_data.groupby(['Season' , 'toss_decision']).size())
Out[32]:
pandas.core.series.Series
In [33]:
season_toss_count_df = match_data.groupby(['Season' , 'toss_decision']).size().reset_index().rename(columns={0:'count'})
In [34]:
season_toss_count_df
Out[34]:
Season toss_decision count
0 2008 bat 26
1 2008 field 32
2 2009 bat 35
3 2009 field 22
4 2010 bat 39
5 2010 field 21
6 2011 bat 25
7 2011 field 48
8 2012 bat 37
9 2012 field 37
10 2013 bat 45
11 2013 field 31
12 2014 bat 19
13 2014 field 41
14 2015 bat 25
15 2015 field 34
16 2016 bat 11
17 2016 field 49
18 2017 bat 11
19 2017 field 48
In [ ]:
In [35]:
plt.figure(figsize=(10,6))
sns.barplot(x='Season' , y='count' , hue = 'toss_decision' , data = season_toss_count_df)
Out[35]:
<Axes: xlabel='Season', ylabel='count'>

Analyzing whether winning toss implies winning game or not¶

In [36]:
match_data.columns
Out[36]:
Index(['id', 'season', 'city', 'date', 'team1', 'team2', 'toss_winner',
       'toss_decision', 'result', 'dl_applied', 'winner', 'win_by_runs',
       'win_by_wickets', 'player_of_match', 'venue', 'umpire1', 'umpire2',
       'umpire3', 'Season'],
      dtype='object')
In [37]:
match_data[['team1' , 'team2' , 'toss_winner' , 'winner']]
Out[37]:
team1 team2 toss_winner winner
0 Sunrisers Hyderabad Royal Challengers Bangalore Royal Challengers Bangalore Sunrisers Hyderabad
1 Mumbai Indians Rising Pune Supergiant Rising Pune Supergiant Rising Pune Supergiant
2 Gujarat Lions Kolkata Knight Riders Kolkata Knight Riders Kolkata Knight Riders
3 Rising Pune Supergiant Kings XI Punjab Kings XI Punjab Kings XI Punjab
4 Royal Challengers Bangalore Delhi Daredevils Royal Challengers Bangalore Royal Challengers Bangalore
... ... ... ... ...
631 Delhi Daredevils Royal Challengers Bangalore Royal Challengers Bangalore Royal Challengers Bangalore
632 Gujarat Lions Royal Challengers Bangalore Royal Challengers Bangalore Royal Challengers Bangalore
633 Sunrisers Hyderabad Kolkata Knight Riders Kolkata Knight Riders Sunrisers Hyderabad
634 Gujarat Lions Sunrisers Hyderabad Sunrisers Hyderabad Sunrisers Hyderabad
635 Sunrisers Hyderabad Royal Challengers Bangalore Sunrisers Hyderabad Sunrisers Hyderabad

636 rows × 4 columns

In [38]:
match_data['toss_win_game_win'] = np.where(match_data['toss_winner']==match_data['winner'] , 'Yes' , 'No')
In [39]:
match_data.columns
Out[39]:
Index(['id', 'season', 'city', 'date', 'team1', 'team2', 'toss_winner',
       'toss_decision', 'result', 'dl_applied', 'winner', 'win_by_runs',
       'win_by_wickets', 'player_of_match', 'venue', 'umpire1', 'umpire2',
       'umpire3', 'Season', 'toss_win_game_win'],
      dtype='object')
In [40]:
match_data['toss_win_game_win'].value_counts().index
Out[40]:
Index(['Yes', 'No'], dtype='object')
In [41]:
match_data['toss_win_game_win'].value_counts().values
Out[41]:
array([325, 311], dtype=int64)
In [42]:
labels = match_data['toss_win_game_win'].value_counts().index
values = match_data['toss_win_game_win'].value_counts().values

trace = go.Pie(labels= labels, values= values, hole=0.3)

data = [trace]

fig = go.Figure(data = data)

fig.update_traces(hoverinfo='label+percent' , textinfo='label+percent')
In [43]:
fig.show()

Analyzing which team have won the tournament most¶

In [44]:
match_data.columns
Out[44]:
Index(['id', 'season', 'city', 'date', 'team1', 'team2', 'toss_winner',
       'toss_decision', 'result', 'dl_applied', 'winner', 'win_by_runs',
       'win_by_wickets', 'player_of_match', 'venue', 'umpire1', 'umpire2',
       'umpire3', 'Season', 'toss_win_game_win'],
      dtype='object')
In [46]:
match_data['Season'].unique()
Out[46]:
array([2017, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016],
      dtype=int64)
In [49]:
df_2016 = match_data[match_data['Season']==2016]
In [50]:
df_2016
Out[50]:
id season city date team1 team2 toss_winner toss_decision result dl_applied winner win_by_runs win_by_wickets player_of_match venue umpire1 umpire2 umpire3 Season toss_win_game_win
576 577 2016 Mumbai 4/9/2016 Mumbai Indians Rising Pune Supergiants Mumbai Indians bat normal 0 Rising Pune Supergiants 0 9 AM Rahane Wankhede Stadium HDPK Dharmasena CK Nandan NaN 2016 No
577 578 2016 Kolkata 4/10/2016 Delhi Daredevils Kolkata Knight Riders Kolkata Knight Riders field normal 0 Kolkata Knight Riders 0 9 AD Russell Eden Gardens S Ravi C Shamshuddin NaN 2016 Yes
578 579 2016 Chandigarh 4/11/2016 Kings XI Punjab Gujarat Lions Gujarat Lions field normal 0 Gujarat Lions 0 5 AJ Finch Punjab Cricket Association IS Bindra Stadium, ... AK Chaudhary VA Kulkarni NaN 2016 Yes
579 580 2016 Bangalore 4/12/2016 Royal Challengers Bangalore Sunrisers Hyderabad Sunrisers Hyderabad field normal 0 Royal Challengers Bangalore 45 0 AB de Villiers M Chinnaswamy Stadium HDPK Dharmasena VK Sharma NaN 2016 No
580 581 2016 Kolkata 4/13/2016 Kolkata Knight Riders Mumbai Indians Mumbai Indians field normal 0 Mumbai Indians 0 6 RG Sharma Eden Gardens Nitin Menon S Ravi NaN 2016 Yes
581 582 2016 Rajkot 4/14/2016 Rising Pune Supergiants Gujarat Lions Rising Pune Supergiants bat normal 0 Gujarat Lions 0 7 AJ Finch Saurashtra Cricket Association Stadium VA Kulkarni CK Nandan NaN 2016 No
582 583 2016 Delhi 4/15/2016 Kings XI Punjab Delhi Daredevils Delhi Daredevils field normal 0 Delhi Daredevils 0 8 A Mishra Feroz Shah Kotla S Ravi C Shamshuddin NaN 2016 Yes
583 584 2016 Hyderabad 4/16/2016 Sunrisers Hyderabad Kolkata Knight Riders Sunrisers Hyderabad bat normal 0 Kolkata Knight Riders 0 8 G Gambhir Rajiv Gandhi International Stadium, Uppal AK Chaudhary CK Nandan NaN 2016 No
584 585 2016 Mumbai 4/16/2016 Mumbai Indians Gujarat Lions Gujarat Lions field normal 0 Gujarat Lions 0 3 AJ Finch Wankhede Stadium HDPK Dharmasena VK Sharma NaN 2016 Yes
585 586 2016 Chandigarh 4/17/2016 Rising Pune Supergiants Kings XI Punjab Rising Pune Supergiants bat normal 0 Kings XI Punjab 0 6 M Vohra Punjab Cricket Association IS Bindra Stadium, ... S Ravi C Shamshuddin NaN 2016 No
586 587 2016 Bangalore 4/17/2016 Royal Challengers Bangalore Delhi Daredevils Delhi Daredevils field normal 0 Delhi Daredevils 0 7 Q de Kock M Chinnaswamy Stadium VA Kulkarni A Nand Kishore NaN 2016 Yes
587 588 2016 Hyderabad 4/18/2016 Mumbai Indians Sunrisers Hyderabad Sunrisers Hyderabad field normal 0 Sunrisers Hyderabad 0 7 DA Warner Rajiv Gandhi International Stadium, Uppal HDPK Dharmasena VK Sharma NaN 2016 Yes
588 589 2016 Chandigarh 4/19/2016 Kings XI Punjab Kolkata Knight Riders Kolkata Knight Riders field normal 0 Kolkata Knight Riders 0 6 RV Uthappa Punjab Cricket Association IS Bindra Stadium, ... S Ravi C Shamshuddin NaN 2016 Yes
589 590 2016 Mumbai 4/20/2016 Royal Challengers Bangalore Mumbai Indians Mumbai Indians field normal 0 Mumbai Indians 0 6 RG Sharma Wankhede Stadium AK Chaudhary CK Nandan NaN 2016 Yes
590 591 2016 Rajkot 4/21/2016 Gujarat Lions Sunrisers Hyderabad Sunrisers Hyderabad field normal 0 Sunrisers Hyderabad 0 10 B Kumar Saurashtra Cricket Association Stadium K Bharatan HDPK Dharmasena NaN 2016 Yes
591 592 2016 Pune 4/22/2016 Royal Challengers Bangalore Rising Pune Supergiants Rising Pune Supergiants field normal 0 Royal Challengers Bangalore 13 0 AB de Villiers Maharashtra Cricket Association Stadium CB Gaffaney VK Sharma NaN 2016 No
592 593 2016 Delhi 4/23/2016 Delhi Daredevils Mumbai Indians Mumbai Indians field normal 0 Delhi Daredevils 10 0 SV Samson Feroz Shah Kotla S Ravi C Shamshuddin NaN 2016 No
593 594 2016 Hyderabad 4/23/2016 Kings XI Punjab Sunrisers Hyderabad Sunrisers Hyderabad field normal 0 Sunrisers Hyderabad 0 5 Mustafizur Rahman Rajiv Gandhi International Stadium, Uppal AK Chaudhary CK Nandan NaN 2016 Yes
594 595 2016 Rajkot 4/24/2016 Royal Challengers Bangalore Gujarat Lions Royal Challengers Bangalore bat normal 0 Gujarat Lions 0 6 V Kohli Saurashtra Cricket Association Stadium K Bharatan BNJ Oxenford NaN 2016 No
595 596 2016 Pune 4/24/2016 Rising Pune Supergiants Kolkata Knight Riders Kolkata Knight Riders field normal 0 Kolkata Knight Riders 0 2 SA Yadav Maharashtra Cricket Association Stadium CB Gaffaney A Nand Kishore NaN 2016 Yes
596 597 2016 Chandigarh 4/25/2016 Mumbai Indians Kings XI Punjab Kings XI Punjab field normal 0 Mumbai Indians 25 0 PA Patel Punjab Cricket Association IS Bindra Stadium, ... Nitin Menon RJ Tucker NaN 2016 No
597 598 2016 Hyderabad 4/26/2016 Sunrisers Hyderabad Rising Pune Supergiants Rising Pune Supergiants field normal 1 Rising Pune Supergiants 34 0 AB Dinda Rajiv Gandhi International Stadium, Uppal AY Dandekar CK Nandan NaN 2016 Yes
598 599 2016 Delhi 4/27/2016 Gujarat Lions Delhi Daredevils Delhi Daredevils field normal 0 Gujarat Lions 1 0 CH Morris Feroz Shah Kotla M Erasmus S Ravi NaN 2016 No
599 600 2016 Mumbai 4/28/2016 Kolkata Knight Riders Mumbai Indians Mumbai Indians field normal 0 Mumbai Indians 0 6 RG Sharma Wankhede Stadium Nitin Menon RJ Tucker NaN 2016 Yes
600 601 2016 Pune 4/29/2016 Rising Pune Supergiants Gujarat Lions Gujarat Lions field normal 0 Gujarat Lions 0 3 DR Smith Maharashtra Cricket Association Stadium CB Gaffaney BNJ Oxenford NaN 2016 Yes
601 602 2016 Delhi 4/30/2016 Delhi Daredevils Kolkata Knight Riders Kolkata Knight Riders field normal 0 Delhi Daredevils 27 0 CR Brathwaite Feroz Shah Kotla KN Ananthapadmanabhan M Erasmus NaN 2016 No
602 603 2016 Hyderabad 4/30/2016 Sunrisers Hyderabad Royal Challengers Bangalore Royal Challengers Bangalore field normal 0 Sunrisers Hyderabad 15 0 DA Warner Rajiv Gandhi International Stadium, Uppal AK Chaudhary HDPK Dharmasena NaN 2016 No
603 604 2016 Rajkot 5/1/2016 Kings XI Punjab Gujarat Lions Gujarat Lions field normal 0 Kings XI Punjab 23 0 AR Patel Saurashtra Cricket Association Stadium BNJ Oxenford VK Sharma NaN 2016 No
604 605 2016 Pune 5/1/2016 Rising Pune Supergiants Mumbai Indians Mumbai Indians field normal 0 Mumbai Indians 0 8 RG Sharma Maharashtra Cricket Association Stadium AY Dandekar RJ Tucker NaN 2016 Yes
605 606 2016 Bangalore 5/2/2016 Royal Challengers Bangalore Kolkata Knight Riders Kolkata Knight Riders field normal 0 Kolkata Knight Riders 0 5 AD Russell M Chinnaswamy Stadium M Erasmus S Ravi NaN 2016 Yes
606 607 2016 Rajkot 5/3/2016 Gujarat Lions Delhi Daredevils Delhi Daredevils field normal 0 Delhi Daredevils 0 8 RR Pant Saurashtra Cricket Association Stadium CB Gaffaney BNJ Oxenford NaN 2016 Yes
607 608 2016 Kolkata 5/4/2016 Kolkata Knight Riders Kings XI Punjab Kings XI Punjab field normal 0 Kolkata Knight Riders 7 0 AD Russell Eden Gardens AK Chaudhary HDPK Dharmasena NaN 2016 No
608 609 2016 Delhi 5/5/2016 Delhi Daredevils Rising Pune Supergiants Rising Pune Supergiants field normal 0 Rising Pune Supergiants 0 7 AM Rahane Feroz Shah Kotla C Shamshuddin RJ Tucker NaN 2016 Yes
609 610 2016 Hyderabad 5/6/2016 Gujarat Lions Sunrisers Hyderabad Sunrisers Hyderabad field normal 0 Sunrisers Hyderabad 0 5 B Kumar Rajiv Gandhi International Stadium, Uppal M Erasmus S Ravi NaN 2016 Yes
610 611 2016 Bangalore 5/7/2016 Rising Pune Supergiants Royal Challengers Bangalore Royal Challengers Bangalore field normal 0 Royal Challengers Bangalore 0 7 V Kohli M Chinnaswamy Stadium CB Gaffaney BNJ Oxenford NaN 2016 Yes
611 612 2016 Chandigarh 5/7/2016 Kings XI Punjab Delhi Daredevils Delhi Daredevils field normal 0 Kings XI Punjab 9 0 MP Stoinis Punjab Cricket Association IS Bindra Stadium, ... HDPK Dharmasena CK Nandan NaN 2016 No
612 613 2016 Visakhapatnam 5/8/2016 Sunrisers Hyderabad Mumbai Indians Mumbai Indians field normal 0 Sunrisers Hyderabad 85 0 A Nehra Dr. Y.S. Rajasekhara Reddy ACA-VDCA Cricket St... S Ravi C Shamshuddin NaN 2016 No
613 614 2016 Kolkata 5/8/2016 Kolkata Knight Riders Gujarat Lions Gujarat Lions field normal 0 Gujarat Lions 0 5 P Kumar Eden Gardens M Erasmus RJ Tucker NaN 2016 Yes
614 615 2016 Chandigarh 5/9/2016 Royal Challengers Bangalore Kings XI Punjab Kings XI Punjab field normal 0 Royal Challengers Bangalore 1 0 SR Watson Punjab Cricket Association IS Bindra Stadium, ... AK Chaudhary HDPK Dharmasena NaN 2016 No
615 616 2016 Visakhapatnam 5/10/2016 Sunrisers Hyderabad Rising Pune Supergiants Sunrisers Hyderabad bat normal 0 Sunrisers Hyderabad 4 0 A Zampa Dr. Y.S. Rajasekhara Reddy ACA-VDCA Cricket St... CB Gaffaney VK Sharma NaN 2016 Yes
616 617 2016 Bangalore 5/11/2016 Royal Challengers Bangalore Mumbai Indians Mumbai Indians field normal 0 Mumbai Indians 0 6 KH Pandya M Chinnaswamy Stadium AY Dandekar C Shamshuddin NaN 2016 Yes
617 618 2016 Hyderabad 5/12/2016 Sunrisers Hyderabad Delhi Daredevils Delhi Daredevils field normal 0 Delhi Daredevils 0 7 CH Morris Rajiv Gandhi International Stadium, Uppal K Bharatan M Erasmus NaN 2016 Yes
618 619 2016 Visakhapatnam 5/13/2016 Mumbai Indians Kings XI Punjab Mumbai Indians bat normal 0 Kings XI Punjab 0 7 MP Stoinis Dr. Y.S. Rajasekhara Reddy ACA-VDCA Cricket St... HDPK Dharmasena CK Nandan NaN 2016 No
619 620 2016 Bangalore 5/14/2016 Royal Challengers Bangalore Gujarat Lions Gujarat Lions field normal 0 Royal Challengers Bangalore 144 0 AB de Villiers M Chinnaswamy Stadium AY Dandekar VK Sharma NaN 2016 No
620 621 2016 Kolkata 5/14/2016 Rising Pune Supergiants Kolkata Knight Riders Rising Pune Supergiants bat normal 1 Kolkata Knight Riders 0 8 YK Pathan Eden Gardens A Nand Kishore BNJ Oxenford NaN 2016 No
621 622 2016 Chandigarh 5/15/2016 Kings XI Punjab Sunrisers Hyderabad Kings XI Punjab bat normal 0 Sunrisers Hyderabad 0 7 HM Amla Punjab Cricket Association IS Bindra Stadium, ... KN Ananthapadmanabhan M Erasmus NaN 2016 No
622 623 2016 Visakhapatnam 5/15/2016 Mumbai Indians Delhi Daredevils Delhi Daredevils field normal 0 Mumbai Indians 80 0 KH Pandya Dr. Y.S. Rajasekhara Reddy ACA-VDCA Cricket St... Nitin Menon CK Nandan NaN 2016 No
623 624 2016 Kolkata 5/16/2016 Kolkata Knight Riders Royal Challengers Bangalore Royal Challengers Bangalore field normal 0 Royal Challengers Bangalore 0 9 V Kohli Eden Gardens CB Gaffaney A Nand Kishore NaN 2016 Yes
624 625 2016 Visakhapatnam 5/17/2016 Delhi Daredevils Rising Pune Supergiants Rising Pune Supergiants field normal 1 Rising Pune Supergiants 19 0 AB Dinda Dr. Y.S. Rajasekhara Reddy ACA-VDCA Cricket St... Nitin Menon C Shamshuddin NaN 2016 Yes
625 626 2016 Bangalore 5/18/2016 Royal Challengers Bangalore Kings XI Punjab Kings XI Punjab field normal 1 Royal Challengers Bangalore 82 0 V Kohli M Chinnaswamy Stadium KN Ananthapadmanabhan M Erasmus NaN 2016 No
626 627 2016 Kanpur 5/19/2016 Kolkata Knight Riders Gujarat Lions Gujarat Lions field normal 0 Gujarat Lions 0 6 DR Smith Green Park AK Chaudhary CK Nandan NaN 2016 Yes
627 628 2016 Raipur 5/20/2016 Sunrisers Hyderabad Delhi Daredevils Delhi Daredevils field normal 0 Delhi Daredevils 0 6 KK Nair Shaheed Veer Narayan Singh International Stadium A Nand Kishore BNJ Oxenford NaN 2016 Yes
628 629 2016 Visakhapatnam 5/21/2016 Kings XI Punjab Rising Pune Supergiants Kings XI Punjab bat normal 0 Rising Pune Supergiants 0 4 MS Dhoni Dr. Y.S. Rajasekhara Reddy ACA-VDCA Cricket St... HDPK Dharmasena Nitin Menon NaN 2016 No
629 630 2016 Kanpur 5/21/2016 Mumbai Indians Gujarat Lions Gujarat Lions field normal 0 Gujarat Lions 0 6 SK Raina Green Park AK Chaudhary CK Nandan NaN 2016 Yes
630 631 2016 Kolkata 5/22/2016 Kolkata Knight Riders Sunrisers Hyderabad Sunrisers Hyderabad field normal 0 Kolkata Knight Riders 22 0 YK Pathan Eden Gardens KN Ananthapadmanabhan M Erasmus NaN 2016 No
631 632 2016 Raipur 5/22/2016 Delhi Daredevils Royal Challengers Bangalore Royal Challengers Bangalore field normal 0 Royal Challengers Bangalore 0 6 V Kohli Shaheed Veer Narayan Singh International Stadium A Nand Kishore BNJ Oxenford NaN 2016 Yes
632 633 2016 Bangalore 5/24/2016 Gujarat Lions Royal Challengers Bangalore Royal Challengers Bangalore field normal 0 Royal Challengers Bangalore 0 4 AB de Villiers M Chinnaswamy Stadium AK Chaudhary HDPK Dharmasena NaN 2016 Yes
633 634 2016 Delhi 5/25/2016 Sunrisers Hyderabad Kolkata Knight Riders Kolkata Knight Riders field normal 0 Sunrisers Hyderabad 22 0 MC Henriques Feroz Shah Kotla M Erasmus C Shamshuddin NaN 2016 No
634 635 2016 Delhi 5/27/2016 Gujarat Lions Sunrisers Hyderabad Sunrisers Hyderabad field normal 0 Sunrisers Hyderabad 0 4 DA Warner Feroz Shah Kotla M Erasmus CK Nandan NaN 2016 Yes
635 636 2016 Bangalore 5/29/2016 Sunrisers Hyderabad Royal Challengers Bangalore Sunrisers Hyderabad bat normal 0 Sunrisers Hyderabad 8 0 BCJ Cutting M Chinnaswamy Stadium HDPK Dharmasena BNJ Oxenford NaN 2016 Yes
In [51]:
df_2016.tail()
Out[51]:
id season city date team1 team2 toss_winner toss_decision result dl_applied winner win_by_runs win_by_wickets player_of_match venue umpire1 umpire2 umpire3 Season toss_win_game_win
631 632 2016 Raipur 5/22/2016 Delhi Daredevils Royal Challengers Bangalore Royal Challengers Bangalore field normal 0 Royal Challengers Bangalore 0 6 V Kohli Shaheed Veer Narayan Singh International Stadium A Nand Kishore BNJ Oxenford NaN 2016 Yes
632 633 2016 Bangalore 5/24/2016 Gujarat Lions Royal Challengers Bangalore Royal Challengers Bangalore field normal 0 Royal Challengers Bangalore 0 4 AB de Villiers M Chinnaswamy Stadium AK Chaudhary HDPK Dharmasena NaN 2016 Yes
633 634 2016 Delhi 5/25/2016 Sunrisers Hyderabad Kolkata Knight Riders Kolkata Knight Riders field normal 0 Sunrisers Hyderabad 22 0 MC Henriques Feroz Shah Kotla M Erasmus C Shamshuddin NaN 2016 No
634 635 2016 Delhi 5/27/2016 Gujarat Lions Sunrisers Hyderabad Sunrisers Hyderabad field normal 0 Sunrisers Hyderabad 0 4 DA Warner Feroz Shah Kotla M Erasmus CK Nandan NaN 2016 Yes
635 636 2016 Bangalore 5/29/2016 Sunrisers Hyderabad Royal Challengers Bangalore Sunrisers Hyderabad bat normal 0 Sunrisers Hyderabad 8 0 BCJ Cutting M Chinnaswamy Stadium HDPK Dharmasena BNJ Oxenford NaN 2016 Yes
In [55]:
df_2016['winner'].tail(1).values[0]
Out[55]:
'Sunrisers Hyderabad'
In [ ]:
In [60]:
winners_team={}

for year in sorted(match_data['Season'].unique()):
    current_yr_df = match_data[match_data['Season']==year]
    winners_team[year] = current_yr_df['winner'].tail(1).values[0]
In [61]:
winners_team
Out[61]:
{2008: 'Rajasthan Royals',
 2009: 'Deccan Chargers',
 2010: 'Chennai Super Kings',
 2011: 'Chennai Super Kings',
 2012: 'Kolkata Knight Riders',
 2013: 'Mumbai Indians',
 2014: 'Kolkata Knight Riders',
 2015: 'Mumbai Indians',
 2016: 'Sunrisers Hyderabad',
 2017: 'Mumbai Indians'}
In [63]:
winners_team.values()
Out[63]:
dict_values(['Rajasthan Royals', 'Deccan Chargers', 'Chennai Super Kings', 'Chennai Super Kings', 'Kolkata Knight Riders', 'Mumbai Indians', 'Kolkata Knight Riders', 'Mumbai Indians', 'Sunrisers Hyderabad', 'Mumbai Indians'])
In [62]:
from collections import Counter
In [64]:
Counter(winners_team.values())
Out[64]:
Counter({'Rajasthan Royals': 1,
         'Deccan Chargers': 1,
         'Chennai Super Kings': 2,
         'Kolkata Knight Riders': 2,
         'Mumbai Indians': 3,
         'Sunrisers Hyderabad': 1})

Comparative analysis of teams - most number of wins¶

In [65]:
match_data.columns
Out[65]:
Index(['id', 'season', 'city', 'date', 'team1', 'team2', 'toss_winner',
       'toss_decision', 'result', 'dl_applied', 'winner', 'win_by_runs',
       'win_by_wickets', 'player_of_match', 'venue', 'umpire1', 'umpire2',
       'umpire3', 'Season', 'toss_win_game_win'],
      dtype='object')
In [66]:
match_data[['team1' , 'team2']]
Out[66]:
team1 team2
0 Sunrisers Hyderabad Royal Challengers Bangalore
1 Mumbai Indians Rising Pune Supergiant
2 Gujarat Lions Kolkata Knight Riders
3 Rising Pune Supergiant Kings XI Punjab
4 Royal Challengers Bangalore Delhi Daredevils
... ... ...
631 Delhi Daredevils Royal Challengers Bangalore
632 Gujarat Lions Royal Challengers Bangalore
633 Sunrisers Hyderabad Kolkata Knight Riders
634 Gujarat Lions Sunrisers Hyderabad
635 Sunrisers Hyderabad Royal Challengers Bangalore

636 rows × 2 columns

In [69]:
matches_played = match_data['team1'].value_counts() + match_data['team2'].value_counts()
In [71]:
type(matches_played)
Out[71]:
pandas.core.series.Series
In [74]:
matches_played_df = matches_played.to_frame().reset_index()
In [75]:
matches_played_df.columns = ['team_name' , 'Matches_played']
In [76]:
matches_played_df
Out[76]:
team_name Matches_played
0 Chennai Super Kings 131
1 Deccan Chargers 75
2 Delhi Daredevils 147
3 Gujarat Lions 30
4 Kings XI Punjab 148
5 Kochi Tuskers Kerala 14
6 Kolkata Knight Riders 148
7 Mumbai Indians 157
8 Pune Warriors 46
9 Rajasthan Royals 118
10 Rising Pune Supergiant 16
11 Rising Pune Supergiants 14
12 Royal Challengers Bangalore 152
13 Sunrisers Hyderabad 76
In [ ]:
In [82]:
wins = pd.DataFrame(match_data['winner'].value_counts()).reset_index()
In [83]:
wins.columns = ['team_name' , 'Wins']
In [84]:
wins
Out[84]:
team_name Wins
0 Mumbai Indians 92
1 Chennai Super Kings 79
2 Kolkata Knight Riders 77
3 Royal Challengers Bangalore 73
4 Kings XI Punjab 70
5 Rajasthan Royals 63
6 Delhi Daredevils 62
7 Sunrisers Hyderabad 42
8 Deccan Chargers 29
9 Gujarat Lions 13
10 Pune Warriors 12
11 Rising Pune Supergiant 10
12 Kochi Tuskers Kerala 6
13 Rising Pune Supergiants 5
In [ ]:
In [86]:
played = matches_played_df.merge(wins, on='team_name' , how='inner')
In [87]:
played
Out[87]:
team_name Matches_played Wins
0 Chennai Super Kings 131 79
1 Deccan Chargers 75 29
2 Delhi Daredevils 147 62
3 Gujarat Lions 30 13
4 Kings XI Punjab 148 70
5 Kochi Tuskers Kerala 14 6
6 Kolkata Knight Riders 148 77
7 Mumbai Indians 157 92
8 Pune Warriors 46 12
9 Rajasthan Royals 118 63
10 Rising Pune Supergiant 16 10
11 Rising Pune Supergiants 14 5
12 Royal Challengers Bangalore 152 73
13 Sunrisers Hyderabad 76 42
In [ ]:
In [90]:
trace1 = go.Bar(
    x = played['team_name'] ,
    y = played['Matches_played'] ,
    name = 'Total Matches'
)

trace2 = go.Bar(
    x = played['team_name'] ,
    y = played['Wins'] ,
    name = 'Matches won'
)
In [91]:
data = [trace1 , trace2]
In [92]:
iplot(data)